Bike Share Map

Bike Share Map shows the locations of docking stations associated with bicycle sharing systems from 400+ cities around the world. Each docking station is represented by a circle, its size and colour depending on the size and number of bicycles currently in it. The maps generally update every few minutes. There is a version that replays the last 48 hours of colour and size changes. In many cities, an ebb and flow of cycle commuters can be seen. Bike Share Map is complemented by a UK bikeshare news blog, Bikesharp.

See it Live

About the Map

Bike Share Map was born out of wanting to visualise the shiny new London Barclays Cycle Hire bikesharing system (now known as Santander Cycles), which appeared in July 2010, shortly after I joined UCL CASA. The operator’s own map wasn’t very useful (it’s improved but still not great). I reused some code from an election visualisation (where circles were used to provide a balanced view across multiple constituencies) and got the system up running in a few days. Someone found out about it who lived in Minneapolis, and wanted to do the same for the NiceRideMN system there. I realised quite quickly that the two systems were built with the same technology, so the same data was available. Washington DC was Number 3, and it then went on from there.

There were data access issues with some systems (e.g. Paris and Brussels) but these days, such issues have been largely overcome, with the recent unveiling of the JCDecaux developer portal and Barcelona City Council making their feed available. B-cycle, who run many small systems in the US, have also been very helpful. I would still love to get more information on Chinese systems though…

I’ve continued to tweak and evolve the look of the site, adding a “Timeline” view in September 2010 that replays the last 48 hours of docking station changes, and most recently (June 2013) launched a global view of all the systems I am monitoring, which is has gradually increased from just under 100 to over 300 – there are more than 1500 systems in the world though, so this remains a snapshot.

Notes

The data is normally collected, and the visualisation updated, every two minutes. Some systems, which require requesting the status of each docking station individually, or appear to be on servers that struggle with repeated requests, are collected every ten minutes or even less frequently than that.

Bike usage numbers, where quoted, are simultaneous usage and normally include cycle redistribution. Actual total usage across the day will be much higher. Total bikes available doesn’t include bikes in use (obviously) but also doesn’t include bikes that are broken (if this information is available) or are being repaired or being redistributed. This is why the number showing is often lower – sometimes much lower – that the operator’s official statistic on the size of the system.

The distribution imbalance graph shows the number of cycles that would need to be moved to a different stand, in order for all stands to be the same % full. Higher numbers indicate a more unbalanced distribution, e.g. many bikes in the centre, few on the edge. It’s an interesting metric for understanding how “stressed” the system is.

This website is run on an academic development server and so is subject to occasional interruption. Please don’t rely on it for finding bikes or spaces!

Credits

Data: Generally the operator’s or city authority’s website, or via their official API where provided, particularly if the operator provides an industry standard GBFS-format feed. For some cities I use a third party – most notably citybik.es, an excellent third-party data collector using PyBikes.

Background map: Data is Copyright OpenStreetMap contributors. For some cities I use HERE maps as a background. For the OSM mapping, I use Mapnik, and the website itself makes heavy use of OpenLayers 4 (amazing web API for drawing those circles).

Why’s my city missing?

There are 1500+ cities and other places with bikesharing systems, but the global map only lists ~300. Here’s why a particular city might not be there:

The system is not a “third/fourth generation bikesharing system” – that is, one with automated, computer controlled docking stations (or dockless bikes) and designed for sharing of bikes, i.e. encouraging short uses of typically an hour or less. Example: University long-rental systems, coin-slot systems.

The system doesn’t make available the necessary information on the web. The information needs to include an API, or a map with vector points (typically a Google Map) showing the locations of the docking stations, plus information on how many bikes are currently in each docking station. Example: Hangzhou.

The system doesn’t display the exact number of bikes at each docking station. Example: Most of the German systems.

The system is too small for interesting spatial analysis research. I generally don’t including systems which have less than six active docking stations, unless they are in the UK. Example: Pavia.

The system doesn’t currently have any bikes in it that are available for use, e.g. it hasn’t launched yet. Example: Athens Keratsini.

The data is extremely unreliable, although I might persevere if it’s a very large system.

The operator has been particularly proactive at stopping third-party reuse of the information, such as a third-party map like this. Example: Stockholm, Bicincitta systems in Italy, many systems in China.

I don’t know about the system. If your city it doesn’t fall into any of the above categories, then let me know about it in the comments box below!

For a comprehensive world map of bikeshare systems, see Bikesharing World Map curated by R. Meddin & P. De Maio.

Why’s my data on here?

Please email me at o.obrien (@) outlook.com to let me know your concerns. I am happy to stop collecting your data if desired, although only publicly accessible webpages and APIs are being used.

I would like a specially enhanced version for my city (e.g. for redistribution)

Please email me at o.obrien (@) outlook.com.

Is the code open source?

No, because it’s pretty untidy and not particularly well designed under the hood. If you are really keen you can see the client-side source code, at least just by viewing source in your browser. There are two other projects which are open source and are building a unified system for collecting data from bike sharing systems around the world: PyBikes (Python) and Bicyclette (Objective-C). I use Python to collect the data myself into a MySQL database, and PHP and Javascript to display it.

Why do you do this?

The visualisation can be considered to be a auxiliary benefit of collecting data on bikesharing systems, which was used for research at UCL, by myself and some colleagues. It was useful for me, to check that the data coming in is good. Subsequently, the map has proven popular in its own right, so I have continued to maintain and update it as a general service to system users and the bikesharing community in general. Please note it is self-supported and hosted on an external server, and so liable to disappear at any time.

What about individual journeys?

Some operators or cities make available files containing individual journey data, normally every few months. These datasets aren’t used in this website, but I still collect them for use in current and future research.

Contact

You can contact me via Twitter or by emailing me at: o.obrien (@) outlook.com on Twitter at @oobr – or leave a comment below.

Nice initiative, though you are missing lots of places obviously even with the criteria mentioned above. But for starters I would suggest adding the Netherlands at least – its only the most cycled city in the world, and with bike sharing programs in various cities not to mention the rentable bikes from the nationwide train service (NS). So dig into that. and I’m sure with all the feedback here you will be expanding daily! =)

Thanks Karl. Unfortuantely Nextbike systems don’t report the precise numbers of bikes at a docking station – if there’s 5 or more, they just say 5+. Therefore it’s difficult to visualise movements of bikes around the docking stations. Hence they are not included.

I understand the issue with Nextbike. But why are you not including Call a Bike ( http://www.callabike-interaktiv.de/ ) which is the system of Deutsche Bahn, and available in many German cities. Their map indeed shows exact numbers, and – if not via API – are available via JSON scraping.

The Call a Bike interactive map is quite new – believe me I looked for it at various phases of expanding the map. Unfortunately it looks like it’s quite a lot of work to actually get hold of the data – it’s not a simple JSON scrape but looks like it needs carefully crafted post requests. If a 3rd party puts this data in a more accessible form then i will be happy to add it.

Ah, that’s disappointing – I just dropped by to let you know that Glasgow’s bike hire system launches tomorrow – but as it’s operated by Nextbike, I guess that means it’s not going to be easy to include it on your site.

It’s great to see a lot of this data becoming open for public use and research!

Personally, I would really like to use this kind of data in my own research on modeling spatiotemporal phenomena and study the spatial and temporal relationships that can be learned from this type of data.
Therefore however I would need historical data (ex. station usage per 15 minutes in the last year), not just live data. The JCDecaux developer portal doesn’t seem to offer that. Is there any service or portal that offers this kind of data, any plan for a portal to do so in the future, or a website/database (or plan) that logs the live data?

Hi, what do I need to do so that the bike sharing system from Vilamoura (Algarve / Portugal) show’s on the map? Do you need database access, API interface or other data ? Thanks in advance for your time

If you need any help, I’d be happy to be of service. I work for Serttel, the company responsible for all bike sharing technology in Brazil and we have many other important cities that still don’t show up in your amazing map.

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You may want to look into whether Rome’s system is still active. I just returned from a trip there…I saw several of the docking stations, but not a single bike. The stations seem to have been given over to motorbike parking.

Just so you know, we have a couple other bikeshare systems that might be of your interest:

Salvador (currently 30 stations, will have 70)
Petrolina (currently 10 stations, no current plans to expand)

Other than that, we’re excited about Rio’s expansion, which starts this month: 200 more stations, though it’s going to be a very slow process! São Paulo is growing fast, and should have 300 stations by the end of 2014.

Recife’s already saturated, and we’re starting to consider expansion plans. The city is almost 100% flat and has a very cycling-friendly climate.

Thanks again, Pedro! I’ve now added in Salvador and Petrolina. It’s great to see so many systems in Brazil, it really lights up the global map now at http://bikes.oobrien.com/ – I look forward especially to São Paulo’s continuing expansion.

More news from Brazil: we just started operating our newest city, Aracaju. We’re starting with 5 stations but should have a full 20 working by June. Here’s the map: http://www.cajubike.com/Default.aspx

Furthermore, we’re hoping to adding a couple more cities to the service, including our first international city!

Hi again Pedro. Great to hear. I’ll look to adding in Aracaju in due course, once it becomes larger, although it looks like the file format is different to the others. Also great to hear about a couple more cities on the way.

Thanks Phil. Unfortunately most NextBike systems (except ones using their newest technology) don’t show the exact numbers of bikes at docking stations, if it’s more than 4 – this makes it not particularly useful for O/D analysis, unfortunately.

This doesn’t necessarily preclude me adding them in at some point but it does mean they are in the lower down in the priority list.

Hi Daniel
Great map!! I am a student at Ryerson University studying Applied Digital Geography and GIS. I am in the process of making a web app for one of my assignments and would like to use the live feed from the Toronto Open City Data portal of the bike share locations http://www.bikesharetoronto.com/data/stations/bikeStations.xml. I have tried adding this live feed but with no luck. I am building an app using the Esri Leaflet api and incorporation layers from CartoDB. This may be very cheeky but I just wanted to know if this is the georss feed that you are using or something else. Any advice would be appreciated!
Kind regard
Kathy

OK I think I understand now. The feed isn’t designed to be put straight into a GIS or web mapping applications, because it’s not a “geo” feed – rather, a regular feed which happens to have some geo information on it. In theory, you could apply a custom XSLT transformation in order to turn it into a GeoRSS or other XML-based geo feed, which might then work. I’ve never done this myself unfortunately. I consume the data into a database and also create a custom CSV file, which is then read in by my map – this is all custom though, I’m not using any geo standards, although I’m considering rewriting my CSV as GeoJSON if I get some time over the forthcoming break. Re ESRI Leaflet plugin, I’ve not used it but it’s this: https://github.com/Esri/esri-leaflet

Thanks, Gustavo. Unfortunately Mobilicade has blocked access to all its websites, from University College London computers, so I am unable to access the Bicicletar website or add it to the Bike Share Map 🙁

Hi
I’m wondering why Pisa is featured, although you specified that its operator bicincitta is very proactive in limiting the usage of their data. I was about to complain on their facebook page about this unfriendly behaviour of theirs, then I noted this seemly contradiction.
By the way, nice work. We work in transportation planning here in Switzerland and were delighted to discover the bicicle map, even though only Luzern is shown.
ciao

Operator policies change – currently only the South America operator is actively blocking me (and indeed all of UCL) which means the systems there are being shown via a third party. I would like to fix some of the changed Italian systems and add in other systems, e.g other Swiss ones, but the map is just run as a hobby and my time is rather limited at the moment. I am hoping to be able to do more later this summer though.

I’m wondering if there’s a way to bring back the chart showing the bicycles in docks over the last 24 hours. The overnight value of this is a good way to get a good estimate of the number of bicycles in use in the system. Without that chart, we must simply speculate about the number of bikes in use or use the reported number from system operators, which is usually much lower and varies from operator to operator.

Hi Jacob, the maps are intended as visualisations of the movements, and are not intended for quantitative analysis/use – hence why I am gradually removing the graphing/numeric information from the maps. It’s a significant burden to maintain the system, the more so if people assume it is reporting exact and correct numbers.

You may consider adding City of Hamilton into your list since it matches all of your criteria. It was launched in March 2015 and become one of the most successful bike-share program in Toronto regionhttps://hamilton.socialbicycles.com/

Could you please include SoBi bikes here in California (now in Santa Monica, coming to Long Beach, West Hollywood, Beverly Hills, Culver City & Westwood soon). CycleHop is the operator, but Social Bicycles manages the backend API. Keep up the good work – you have fans here at UCLA (Urban & Regional Planning Dept)!

Thanks – yes I am hoping to have those in soon if there is a suitable data feed. However please note that the API link you sent there is for retrieving individual data about a single user of the system, rather than an overall picture of the system.

Great to know about your efforts to gather bikeshare data from around the world and display the stats in your website. I’m glad to discover your website recently. We are currently operating 11 bikeshare stations in Yas Island, Abu Dhabi and very soon expanding to 50 new stations in the city. We would like to have ADCB Bikeshare on your map.

I am a BSS user from Barcelona and I am personaly interested in the maths behind BSS. Particularly, I would like to study Incentive-Based Rebalancing.

It is great to see the amount of data in the map. I wander if there are metrics on the performance of different cities. Something like a “ranking” of cities with the best balance but maybe it is not easy to define what metrics to use.

You might look at the thesis of Eoin O’Mahony from Cornell, it can be downloaded for free and it seeks to optimise the rebalancing of bicycle numbers for a scheme in New York.

This fellow suggests a way of accessing historical data for the Dublin bike scheme. JCD don’t seem to make historical data available, I am not sure about their motives, but let me know if I am mistaken on this.

Guinness bribe:
I use the bicycle sharing system in Dublin and the stations near my home are invariably bereft of bicycles much of the time from 08:30 until 10:00, and quite sparsely populated for most of the day. The stations become packed after 17:00 and it is difficult to drop off a bicycle then.

I suspect there are major inefficiencies and poorly planned rebalancing here in Dublin. I discussed this with someone who used a scheme in Valencia, Spain, and they never encountered such severe difficulties there.

If anyone can optimise the “rebalancing” act of Dublin bikes I will be very grateful and buy you a Guinness or ten!!

Hi! I found that my city, Budapest is on your map, it’s very great. I would be interested in the numbers of the rented bikes per day, can you do graphs from your data about it? That would be awesome 🙂
Thanks!

What about encircle in Medellín city in Colombia south america?.
Medellín was called the most innovative city in the world, have a map in google map with information about toking stations and bicycles and its a 3rd gen system.

Have you considered quality metrics other than the Distribution Imbalance chart?

For example, if no station ever goes empty, any imbalance doesn’t really matter. (This is assuming the system allows returns to full stations – otherwise, full stations are worse than empty stations.) Although, a group of two may perceive as empty any station with just one bike… Further, an empty station doesn’t matter if nobody wanted to rent a bike there then anyway.

Hi, most systems don’t allow returns to full stations (I know a few do). I agree that the Distribution Imbalance is of limited practical use “on the ground”, i.e. for users, however it offers a relatively simple summary of the state of the whole system and is easily comparable between systems.

here is Pittsburgh’s feed. Its a nextbike system. You’ve probably already learned to ignore the ‘bikes’ attribute and instead subtract ‘free_racks’ from ‘bike_racks’ to determine bike availability using the nextbike feed.

Citibik.es is a third-party API. The official operator, city or technology provider does not provide the data as an API. The technology provider (B-cycle) used to, but not any more it appears. I will investigate whether I can find another source.

First of all, congratulations for the website. As a bike-sharing enthusiast, I love to spend some hours a week to check some systems.
I have one specific question as a researcher. What do you mean and how do you get the values to Med Neigh (D) and Density (D)?
If the first is average distance between stations, it does not coincides with the second. Since a 6 st/km2 is very scattered and would not result in 113 m in spacing (Hangzhou example).
I’d appreciate if you could clarify this 🙂

Hi Yerbol, Load Factor is number of bikes divided by total number of docking stations, expressed as a percentage. Load Factor of 50% = half of the docks have bikes in them and half are empty. Cities generally aim for around 45% however quieter systems or ones with less commuter activity (or quieter times of the year, e.g. winter) can generally go up to around 55%.

Hello! I am Peter Zhuang and I am very happy to tell you about the YouBike public bicycle system in Taipei. Currently in Quanzhou and Putian City in China, it has officially served. I hope that you can include the information of these two cities in these websites.
You can collect your own data just like collecting Taipei data.
Quanzhou website: https://www.youbike.me/cn/index.php
Putian City website: https://putian.youbike.me/cn/index.php

Gijón city (Spain) bikes-sharing system is opered by JCDecaux. It has changed all its bikes (80 ud.) and stations (8 ud.) last month of march 2018. The use of the bikes has increased in an exponential way… Each bike has a rotation rate of 8 rentals a day. What a change !

Don’t know how to contact the admin, but there’s on of these bikes abandoned in Crescent Lane, London SW4 9T, outside No 17. Something’s been ripped off the rear, but it still works. Could this be passed on please so that it can be recovered?

A dockless bike? (orange, yellow or green). If so, I’m afraid that, anecdotally, the operators generally aren’t that bothered about recovering them. If it’s a red bike, then TfL/Serco would I am sure be very grateful to get it back – contact TfL to arrange.

Could you please explain about distribution imbalance a bit. Do you calculate each station’s docks percentage of the whole system? And then you take bikes in-by docks and distribute them according to each station % size? Right?
What is the best practice for relationship between number of docks of a station and required amount of bikes within service area of the station? Number of bikes * 2-2.5 = number of docks?

Why do you exclude OV-fiets? It has 300+ locations in the Netherlands, most of them fully automated. The ‘third/fourth generation’-rule sounds kind of arbitrary, especially combined with ‘typically less then an hour’. OV-fiets is one of the largest bike-sharing systems in the world? Why would you exclude it? Only because the system works slightly different then in countries where ‘normal’ bike use is far lower?